Open yanchvlad opened 6 years ago
I guess you are talking about the reinforcement learning sample. What exactly did you modify in the code ? Or are you saying that the code as it is on GitHub does not work ?
@martin-gorner Sorry about misunderstandings. Yes, I'm talking about reinforcement learning sample. I found out that non-changed sample doesn't work. It happens because of different models are created by name_scope('train') and name_scope('roll_out'). The trained weights are not used in next roll-out operation when train operation is over. And all roll-out operations will always compute actions from non-trained NN. As I found out it happened because of build_graph(observations) call from different name_scopes. When I united these two name_scopes in one, everything worked as it could be (weights were shared and reused).
python 3.6 tensorflow 1.10.0 GPU ver
@yanchvlad Thanks for reporting the issue. This is a known issue that happened between TensorFlow versions 1.8 and 1.9, where the reuse behavior is different for tf.keras models.
For now my suggestion would be either of the following:
a. use TensorFlow version 1.8
or
b. rewrite the build_graph
function to not use tf.keras.layers
.
@yanchvlad if you make the changes before we do please send a pull req!
In my network rollout of next epoch dosen't use trained weights of prev train operation. And I see in tensorboard that rollout and train graph have seperate 'model' and layers with different names (for ex. dense_1, dense_0, dense_2, dence_3).
Where is a problem? I slightly changed code:
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